TY - JOUR

T1 - A phenomenological model of seizure initiation suggests network structure may explain seizure frequency in idiopathic generalised epilepsy

AU - Benjamin, Oscar

AU - Fitzgerald, Thomas H.B.

AU - Ashwin, Peter

AU - Tsaneva-Atanasova, Krasimira

AU - Chowdhury, Fahmida

AU - Richardson, Mark P.

AU - Terry, John R.

N1 - Funding Information:
KTA was supported by an EPSRC grant (EP/I018638/1). OB,PA,KTA and JRT acknowledge the support of the Mathematical Neuroscience Network, funded by the EPSRC.

PY - 2012

Y1 - 2012

N2 - We describe a phenomenological model of seizure initiation, consisting of a bistable switch between stable fixed point and stable limit-cycle attractors. We determine a quasi-analytic formula for the exit time problem for our model in the presence of noise. This formula-which we equate to seizure frequency-is then validated numerically, before we extend our study to explore the combined effects of noise and network structure on escape times. Here, we observe that weakly connected networks of 2, 3 and 4 nodes with equivalent first transitive components all have the same asymptotic escape times. We finally extend this work to larger networks, inferred from electroencephalographic recordings from 35 patients with idiopathic generalised epilepsies and 40 controls. Here, we find that network structure in patients correlates with smaller escape times relative to network structures from controls. These initial findings are suggestive that network structure may play an important role in seizure initiation and seizure frequency.

AB - We describe a phenomenological model of seizure initiation, consisting of a bistable switch between stable fixed point and stable limit-cycle attractors. We determine a quasi-analytic formula for the exit time problem for our model in the presence of noise. This formula-which we equate to seizure frequency-is then validated numerically, before we extend our study to explore the combined effects of noise and network structure on escape times. Here, we observe that weakly connected networks of 2, 3 and 4 nodes with equivalent first transitive components all have the same asymptotic escape times. We finally extend this work to larger networks, inferred from electroencephalographic recordings from 35 patients with idiopathic generalised epilepsies and 40 controls. Here, we find that network structure in patients correlates with smaller escape times relative to network structures from controls. These initial findings are suggestive that network structure may play an important role in seizure initiation and seizure frequency.

UR - http://www.scopus.com/inward/record.url?scp=84859486387&partnerID=8YFLogxK

U2 - 10.1186/2190-8567-2-1

DO - 10.1186/2190-8567-2-1

M3 - Article

AN - SCOPUS:84859486387

SN - 2190-8567

VL - 2

JO - Journal of Mathematical Neuroscience

JF - Journal of Mathematical Neuroscience

IS - 1

M1 - 1

ER -